In response to a talk I gave at the bat meetings, some people saw a problem in the experimental design of my partner choice tests, because I had a condition where a bat can’t reciprocate, but not a condition where a bat won’t reciprocate. I do know that hungry bats will beg other hungry bats, but the argument is that I don’t know if they will treat a simultaneously hungry bat that can’t reciprocate in the same way as a bat that won’t reciprocate. And perhaps bats would only “punish” or “abandon” partners that choose not to reciprocate, not those unfortunate bats who fail to reciprocate due to being repeatedly absent or starved themselves.
The first obvious logistical problem is that creating a situation where a bat can reciprocate but won’t is extremely difficult and maybe impossible in practice. But I don’t think this even matters that much because a bat should respond to both can’ts and won’ts, and here’s why.
Imagine you’re a female vampire bat maintaining cooperative social relationships with several other bats. Your time and energy are limited and you should therefore choose wisely with regards to which individuals you target with your social investments (i.e. food sharing and social grooming). Assume that you are equally related to Bat A and B, and that Bat A consistently feeds you when you are hungry. Under which of the following scenarios, should you begin to invest more in Bat A and less in Bat B?
1. Bat B never feeds you even when she has food to give you.
2. Bat B never feeds you because she is always hungry herself.
3. Bat B is never around when you are hungry.
The answer, which seems obvious to me, is that you should prefer bat A over B in all 3 scenarios. That is, under all 3 scenarios, you should invest less time and energy feeding Bat B and instead use that time and energy feeding and grooming Bat A. Now there might be differences between the three scenarios in how long it takes you to start preferring A versus B. You might be far less forgiving of scenario 1 vs scenario 2 and 3, but the basic point is that you should reduce your investment in bat B in all 3 cases.
The problem here is that people sometimes think that you, as the female bat, should only care about scenario 1 because that matches people’s’ notions of “cheating” whereas the others are accidental. Bat B has an excuse so it’s not cheating. People think that it matters a lot whether a bat won’t reciprocate versus whether it can’t reciprocate. I agree there’s a difference, but the difference is quantitative not qualitative.
To the extent that you are a Darwinian agent, your only concern is the probability of an investment leading to a fitness return. If a bat won’t reciprocate, this information will certainly change your prediction of the likelihood of this bat reciprocating in the future. But if a bat can’t reciprocate and it has an excuse (I was not around; I did not feed either), then you would judge this as less informative as to whether that bat would reciprocate in the future. The kind of information you glean is the same, but the information is different. The partner that won’t reciprocate is probably bad social investment; whereas the can’t reciprocate partner *might* be a bad investment (or it might just be a fluke). But in either case, you should remember the event and it should damage (if only very slightly) your relationship with that partner.
If you simulated cheating in Bat B by consistently removing (or fasting) Bat B whenever the subject bat was hungry (i.e. bat B can’t reciprocate), then biological market theory suggests you should certainly see a response, because you have made that partner look worse relative to others. The partner switching response might be faster if the bat won’t reciprocate, but it should come eventually in any case.
What’s a cheat? In the evolution of cooperation literature, authors often talk about “cheats” (reviewed here) to describe an individual that exploits the cooperation of others by gaining the fitness benefits without paying the fitness costs. Talking about “cheats” is often very useful in explaining why evolutionarily stable cooperation often requires some form of conditional enforcement or discrimination. But the term can also create unnecessary confusion for at least two reasons. First, “cheat” sounds like a discrete type, behavior, or trait, whereas much of the time it’s used to describe a scenario with individuals that vary continuously. Imagine if we talked about human prosocial behavior using the terms “cooperators” for anyone who cooperates more than average and “cheats” for anyone who cooperates less than average. Most people (who cooperate to an average degree) would be ambiguous. You can’t model this in the same way you might model conflict between more discrete “types” like males and females or discrete reproductive strategies. This is a problem I see in the behavioral syndromes literature too.
Second, people think “cheating” refers to something cognitive or intentional, rather than just variation in a cooperative trait. This is not such a problem in bacteria or plants, but it can be a big problem in animal cooperation studies. For (hypothetical) example, in a group of vampire bats clustering for warmth, a “cheat” could simply describe an individual that maintains a slightly lower body temperature allowing itself to be warmed by an adjacent body. Two normal bats that cluster together are both paying some cost and receiving a benefit of the other’s warm body. But a normal bat that clusters with a cold cheat is not receiving that benefit, only the cold cheat benefits, and it might be paying a larger cost. In reality, “cold cheats” probably do not exist because of physiological constraints, but the logic still applies. Cheating in this scenario is not a strategic behavior; it’s just a physiological trait.
To be clear, I’m not saying that the distinction between can’t help versus won’t help doesn’t matter. Some authors writing on this topic have argued that it would be very cognitively difficult to distinguish between partners that can’t and won’t reciprocate, and so this might be very rare distinction to make. But in fact precisely such a difference has been demonstrated in cooperatively mobbing birds.
Experimenters first used fake owls to induce cooperative mobbing among 3 mated pairs of pied flycatcher mated pairs. They created experimental triads of three equidistant nestboxes. One pair (the subject pair) was exposed to a fake owl near their nestbox to induce mobbing. The second pair (the defector pair) was held captive (either nearby in a blind or trapped inside their own nestbox) and hence prevented from mobbing. The third pair (the helper pair) was left untreated, such that the helper pair always helped the subjects with mobbing, but defector pair could not. The authors then simultaneously presented the helper and the defector pairs with owls, and tested at which nestbox the subject pair would choose to help. The subjects helped the helper pair more often. In a follow-up experiment, the defector pair was presented with an owl. In most trials, the helper pair, but not the subject pair, joined the defector pair in mobbing. This makes sense because the defectors only defected against the subjects, not the helpers.
Then using the same setup, the experimenters showed that the degree of reciprocity was also sensitive to whether the failure of partners to mob was caused by their absence (“the excuse principle“). To simulate voluntary defection, the experimenters removed the defection pair, but played their alarm calls to simulate their presence. To simulate involuntary absence, the experimenters completely removed the pair during the predator presentation to simulate their absence during the owl attack. There was no sign of their presence at all. When the captured birds appeared present but unwilling to help, the subjects later reciprocated help in only 2 of 20 cases, but when captured pair was completely absent, the subject pair reciprocated help in 20 of 21 cases.
This is a great experiment. But it does not suggest that the birds will forgive indefinitely. I think we can be fairly confident that if the absent birds were consistently and repeatedly absent whenever an owl showed up. The subjects would begin to reduce their help towards those partners as well, because repeated “voluntary defection” and “unintentional absence” are just two different ways of being a bad cooperative partner.
Alongside the partner’s capacity to help, there are many factors that should influence the degree of contingency in a cooperative exchange. One example is the cost-benefit ratio of the social investment. For example, mobbing birds only help past helpers at fairly distant nestboxes, but when mobbing birds are responding to an owl at a neighboring nestbox that is very close, they always help unconditionally (see here). This is because mobbing an owl that is very close to your own nestbox has a larger immediate selfish benefit (which immediately outweighs the cost of doing nothing), whereas mobbing a more distant owl poses large costs that have to compensated by the relationship you build with the neighboring pair.
Kinship is another factor that can influence the degree of experience-based contingency in helping decisions. Social bonds consisting of multiple cooperative services would decrease the contingency that can be easily measured, because asymmetries in one service can be balanced out with other services.
So now all these interactions begin to get very messy. Because we have multiple factors moving the degree of contingency in opposing directions. Vampire bats make larger social investments in highly bonded partners, which should make contingency very strong. But highly bonded partners might have multiple ways of helping each other (multiple currencies) which makes the measurable contingencies within each currency very weak. Moreover, social bonds tend to form between close relatives, and kinship could conceivably decrease contingency, because investors are compensated indirectly through indirect fitness, or increase contingency, because the larger investments in kin that are not reciprocated are worse than smaller losses. Hopefully, models that integrate kinship, partner choice, and exchange with multiple services will increasingly tackle such complexities to give us some clear predictions.
The one thing we can see for sure is that “tit-for-tat” (where a bat simply remembers only the last round with a single partner and makes a binary “yes” or “no” helping decision within a single service) is not a good model for predicting the pattern of cooperation in vampire bats or probably any long-lived social animal.